Correlation Between Tesla and BorgWarner
Can any of the company-specific risk be diversified away by investing in both Tesla and BorgWarner at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Tesla and BorgWarner into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Tesla Inc and BorgWarner, you can compare the effects of market volatilities on Tesla and BorgWarner and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Tesla with a short position of BorgWarner. Check out your portfolio center. Please also check ongoing floating volatility patterns of Tesla and BorgWarner.
Diversification Opportunities for Tesla and BorgWarner
0.87 | Correlation Coefficient |
Very poor diversification
The 3 months correlation between Tesla and BorgWarner is 0.87. Overlapping area represents the amount of risk that can be diversified away by holding Tesla Inc and BorgWarner in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on BorgWarner and Tesla is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Tesla Inc are associated (or correlated) with BorgWarner. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of BorgWarner has no effect on the direction of Tesla i.e., Tesla and BorgWarner go up and down completely randomly.
Pair Corralation between Tesla and BorgWarner
Given the investment horizon of 90 days Tesla Inc is expected to under-perform the BorgWarner. In addition to that, Tesla is 2.44 times more volatile than BorgWarner. It trades about -0.13 of its total potential returns per unit of risk. BorgWarner is currently generating about -0.09 per unit of volatility. If you would invest 3,152 in BorgWarner on December 29, 2024 and sell it today you would lose (333.00) from holding BorgWarner or give up 10.56% of portfolio value over 90 days.
Time Period | 3 Months [change] |
Direction | Moves Together |
Strength | Strong |
Accuracy | 100.0% |
Values | Daily Returns |
Tesla Inc vs. BorgWarner
Performance |
Timeline |
Tesla Inc |
BorgWarner |
Tesla and BorgWarner Volatility Contrast
Predicted Return Density |
Returns |
Pair Trading with Tesla and BorgWarner
The main advantage of trading using opposite Tesla and BorgWarner positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Tesla position performs unexpectedly, BorgWarner can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in BorgWarner will offset losses from the drop in BorgWarner's long position.The idea behind Tesla Inc and BorgWarner pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.BorgWarner vs. Lear Corporation | BorgWarner vs. Autoliv | BorgWarner vs. Fox Factory Holding | BorgWarner vs. LKQ Corporation |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Sign In To Macroaxis module to sign in to explore Macroaxis' wealth optimization platform and fintech modules.
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